# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# NOTE: This file is auto generated by the elixir code generator program.
# Do not edit this file manually.

defmodule GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Scheduling do
  @moduledoc """
  All parameters related to scheduling of training jobs.

  ## Attributes

  *   `maxRunningTime` (*type:* `String.t`, *default:* `nil`) - Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ```yaml trainingInput: scheduling: maxRunningTime: 7200s ```
  *   `maxWaitTime` (*type:* `String.t`, *default:* `nil`) - Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ```yaml trainingInput: scheduling: maxWaitTime: 3600s ```
  *   `priority` (*type:* `integer()`, *default:* `nil`) - Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.
  """

  use GoogleApi.Gax.ModelBase

  @type t :: %__MODULE__{
          :maxRunningTime => String.t() | nil,
          :maxWaitTime => String.t() | nil,
          :priority => integer() | nil
        }

  field(:maxRunningTime)
  field(:maxWaitTime)
  field(:priority)
end

defimpl Poison.Decoder, for: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Scheduling do
  def decode(value, options) do
    GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Scheduling.decode(value, options)
  end
end

defimpl Poison.Encoder, for: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Scheduling do
  def encode(value, options) do
    GoogleApi.Gax.ModelBase.encode(value, options)
  end
end
